Question

I need help on a simple explanation of this R output:

> head(MF)

X       Date         MNOC    MRTN MGD MSPY

1 1 2007-01-31 -0.014844561 -0.009018188 -0.01940291 -0.028969678

2 2 2007-02-28 -0.031421338 -0.038004244 -0.04271800 0.021903799

3 3 2007-03-31 0.008073055 -0.040789288 -0.04034817 -0.023133782

4 4 2007-04-29 0.002441104 0.218768998 0.04675213 -0.018735156

5 5 2007-05-31 0.007841208 0.260318247 0.01976285 0.032224648

6 6 2007-06-30 0.019367687 0.060879241 -0.03720927 -0.002510906

> tail(MF)

X       Date         MNOC    MRTN MGD MSPY

175 175 2018-07-31 0.02403466 0.12460714 0.017343930 0.01511953

176 176 2018-08-30 -0.03900868 -0.02449022 0.011767990 -0.01674357

177 177 2018-09-30 0.08410069 0.02610793 0.008586856 0.01477178

178 178 2018-10-31 0.02359243 0.03372435 0.031216256 0.02210475

179 179 2018-11-29 0.05481305 0.03559211 0.055869500 0.03619824

180 180 2018-12-30 -0.01580143 0.02489349 0.042022531 0.02163921

> NOC = MF[1:179,3]

> SPY = MF[1:179,6]

> (fitc <- lm(NOC~SPY))

Call:

lm(formula = NOC ~ SPY)

Coefficients:

1.           SPY

-0.0005484    1.1692286

> summary(fitc)

Call:

lm(formula = NOC~ SPY)

Residuals:

     Min       1Q   Median       3Q      Max

-0.26235 -0.03306 -0.00540 0.01924 0.35662

Coefficients:

              Estimate Std. Error t value Pr(>|t|)   

(Intercept) -0.0005483 0.0051696 -0.106    0.916   

SPY          1.1702285 0.1291471   9.125 <2e-16 ***

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.06736 on 177 degrees of freedom

Multiple R-squared: 0.3197, Adjusted R-squared: 0.315

F-statistic: 85.25 on 1 and 177 DF, p-value: < 2.2e-16

Answer 1